Comprehensive transaction cost analysis can become complex and overwhelming. One approach to simplify this task is to use a pre-defined model with parameters calibrated by a third-party provider using tools like MATLAB.

In the current trading environment, investors primarily perform
transaction cost analysis (TCA) by logging into a broker-dealer
or third-party server. These procedures require investors to load
their trade data, portfolio holdings and/or other valuable
investment ideas and proprietary research into these systems to
run analyses. Unfortunately, for investors, these processes could
potentially subject the fund to information leakage and allow
outside persons to reverse engineer valuable investment
processes, resulting in higher trading costs, lower returns and a
decline in the competitive advantage for the fund.

Investors, of course, develop their own trading analytics and/or
install the third party and/or broker models on their own desktop
to eliminate potential information leakage. However, developing a
proprietary trading analytics system is a costly endeavour and
requires on-going research, development and testing. It also
requires a large resource and budget commitment and a large
enough data sample to ensure staatistically accurate models and
results. Additionally, broker-dealer and third-party vendor
systems are not readily capable to be installed on a client
desktop due to proprietary transaction costs analysis (TCA)
formulas and because these analytics need to interact with many
different databases and other systems that reside on the
broker-dealer or third-party vendor system.